Investigating the Role of Systematic and Firm‐Specific Factors in Default Risk: Lessons from Empirically Evaluating Credit Risk Models*

2006 ◽  
Vol 79 (4) ◽  
pp. 1955-1987 ◽  
Author(s):  
Gurdip Bakshi ◽  
Dilip Madan ◽  
Frank Xiaoling Zhang
Keyword(s):  
Credit Risk ◽  
Default Risk ◽  
Risk Models ◽  
Specific Factors

scholarly journals Human capital and credit risk management: training is more valuable than experience

2019 ◽  
Vol 17 (1) ◽  
pp. 67-77
Author(s):  
Ghassen Bouslama ◽  
Christophe Bouteiller
Keyword(s):  
Risk Management ◽  
Human Capital ◽  
Credit Risk ◽  
Default Risk ◽  
Management Training ◽  
Credit Risk Management ◽  
Risk Monitoring ◽  
Loan Officer ◽  
Loan Officers

The aim of this article is to assess how human capital, and more specifically training and experience, helps in forecasting and monitoring credit risk. It uses a survey of a sample of loan officers in a major French mutualist bank and applies analysis of variance and correlation to determine the relationships among variables. The study of these two components of human capital in SME loan officers shows that their ability to anticipate risk depends above all on their training rather than on their experience. Some methods of anticipating risk are more important than others. Loan officers monitor their clients in similar ways, whatever the degree and nature of their experience. The findings have two important implications for credit risk management and human capital: first, both technical and regulatory training is crucial to enable loan officers to anticipate bank credit risk, second, experience, whether in banking or as a loan officer, only makes a difference in monitoring risk. These results will be useful when banks are planning recruitment, career management and resource and skills allocation. They also suggest that staff knowledge management will enable banks to use their human capital effectively to reach their own objectives with regard to risk control, and those fixed by the regulators. This work is, as far as it is known, the first to study the role of human capital in managing credit risk. The authors show that training is more important than experience in default risk anticipation, but that experience is useful in risk monitoring.

Assessment of Credit Risk Models on Rule 144A Corporate Bonds

2018 ◽  
Keyword(s):  
Credit Risk ◽  
Default Risk ◽  
Credit Ratings ◽  
The United States ◽  
Convertible Bonds ◽  
Discrete Models ◽  
Corporate Bond ◽  
Risk Models ◽  
Bond Portfolio ◽  
Portfolio Managers

Accurate assessment of credit risk can improve the performance of bond portfolio managers. Using credit ratings and market-based credit risk models from S&P and Bloomberg, we investigate the performance of four credit risk models in the Rule 144A corporate bond markets in the United States over the 1990–2015 period. The authors divide their sample into straight bonds and convertible bonds and find that (1) when it comes to straight bonds, discrete models such as S&P’s credit ratings and Bloomberg ratings determine yields more accurately than the continuous market-based models of S&P and Bloomberg; (2) with regard to convertible bonds, a convertible option has a stronger effect than credit ratings in determining yields, and only Bloomberg default risk ratings, not S&P credit ratings, determine the yields; (3) for convertible bonds, the continuous market-based models of S&P and Bloomberg affect yields more significantly than discrete models; and (4) when it comes to predicting actual defaults, Bloomberg models are superior to S&P’s models, and the Bloomberg discrete model has more power than its continuous counterpart.

scholarly journals Determinants of Liquidity Considering Role of Market Competition; Evidence from Pakistan’s Banking Sector

2020 ◽  
Vol 2 (2) ◽  
pp. 51-59
Author(s):  
Amir Rafique ◽  
Muhammad Adeel ◽  
Kalsoom Akhtar ◽  
Muhammad Amir Alvi
Keyword(s):  
Credit Risk ◽  
Banking Sector ◽  
Panel Data Analysis ◽  
Market Competition ◽  
Data Set ◽  
Macroeconomic Factors ◽  
Negative Effect ◽  
Specific Factors ◽  
Bank Specific Factors

Current study empirically analyzes bank specific factors and macroeconomic factors that determine the liquidity reserves of banks functioning in Pakistan. To highlight the association, current study performed random effects estimates on a data set of 20 banks from 2006 to 2016.  Bank specific factors include bank size, capital and credit Risk. GDP and Inflation are the macroeconomic factors that were considered. Market competition has been measured through HHI. Based on panel data analysis, current study suggests that bank specific factors (except capital), macroeconomic factors and market competition significantly affect liquidity reserves of banks in Pakistan. These factors include bank size, credit risk, market competition, GDP and inflation. In addition, bank size, credit risk, GDP and Inflation revealed a negative effect on bank liquidity. On the other hand, market competition revealed a positive effect on bank liquidity. Capital showed an insignificant effect on bank liquidity.

scholarly journals Investigating the Sources of Default Risk : Lessons from Empirically Evaluating Credit Risk Models

2001 ◽  
Vol 2001 (15) ◽  
pp. 1-53 ◽  
Author(s):  
Gurdip Bakshi ◽  
◽  
Dilip B. Madan ◽  
Frank X. Zhang
Keyword(s):  
Credit Risk ◽  
Default Risk ◽  
Risk Models

Understanding the Role of Recovery in Default Risk Models : Empirical Comarisons and Implied Recovery Rates

2001 ◽  
Vol 2001 (37) ◽  
pp. 1-37 ◽  
Author(s):  
Gurdip Bakshi ◽  
◽  
Dilip B. Madan ◽  
Frank X. Zhang
Keyword(s):  
Default Risk ◽  
Risk Models ◽  
Recovery Rates

Conditional Giving: The Role of Conflict Specific Factors on Willingness to Sacrifice

2006 ◽  
Author(s):  
Brent A. Mattingly ◽  
Eddie M. Clark ◽  
Kiara J. Weaver ◽  
Tim M. Emge ◽  
Chris K. Adair
Keyword(s):  
Specific Factors ◽  
Willingness To Sacrifice

Physical capital stock, technological upgrading and modernisation in Hungary

2005 ◽  
Vol 55 (2) ◽  
pp. 201-221 ◽  
Author(s):  
Andrea Szalavetz
Keyword(s):  
Capital Accumulation ◽  
Physical Capital ◽  
Developed Countries ◽  
Point Of View ◽  
Technology Generation ◽  
Development Policies ◽  
Specific Factors ◽  
Physical Capital Accumulation

This paper discusses the relation between the quality and quantity indicators of physical capital and modernisation. While international academic literature emphasises the role of intangible factors enabling technology generation and absorption rather than that of physical capital accumulation, this paper argues that the quantity and quality of physical capital are important modernisation factors, particularly in the case of small, undercapitalised countries that recently integrated into the world economy. The paper shows that in Hungary, as opposed to developed countries, the technological upgrading of capital assets was not necessarily accompanied by the upgrading of human capital i.e. the thesis of capital skill complementarity did not apply to the first decade of transformation and capital accumulation in Hungary. Finally, the paper shows that there are large differences between the average technological levels of individual industries. The dualism of the Hungarian economy, which is also manifest in terms of differences in the size of individual industries' technological gaps, is a disadvantage from the point of view of competitiveness. The increasing differences in the size of the technological gaps can be explained not only with industry-specific factors, but also with the weakness of technology and regional development policies, as well as with institutional deficiencies.

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